Interpretive Summary: Dampwood termites of the genus Zootermopsis are an abundant group of basal termites found in temperate forests of western North America. However, it is difficult to tell species and subspecies apart without complex analytical procedures. Access to a fast, economical means of determining species and subspecies would benefit researchers studying population dynamics, and help termite control companies optimize control strategies. We used near-infrared spectroscopy and neural networks to classify Zootermopsis species and subspecies with greater than 99%. The inexpensive, reproducible, and rapid nature of near-infrared spectroscopy makes it a viable alternative to morphological, hydrocarbon, or genetic analysis for identifying Zootermopsis.

Technical Abstract:
Dampwood termites of the genus Zootermopsis are an abundant group of basal termites found in temperate forests of western North America. Three species are currently recognized in the genus and one of these species is subdivided into two subspecies. Although morphological and genetic characters are useful in differentiating among the three species and the two subspecies, respectively, only hydrocarbon analysis can enable differentiation both among the three species and the two subspecies. Due to the limitations of hydrocarbon analysis, such as the need for fresh specimens, alternative methods that could rapidly and accurately identify Zootermopsis would be useful. Using near-infrared spectroscopy, each of the Zootermopsis species and subspecies were identified with greater than 95% and 85% accuracy, respectively. In addition, neural network analysis successfully enabled the identification of the species and subspecies with greater than 99% accuracy. The inexpensive, reproducible, and rapid nature of near-infrared spectroscopy makes it a viable alternative to morphological, hydrocarbon, or genetic analysis for identifying Zootermopsis.